A local AI quant strategy backtesting console built on free data sources, using Zipline and RQAlpha for US stocks and China A-shares.
If you are searching for these topics, this project is designed for you:
- AI quant strategy backtesting
- local quant backtesting platform
- US stock backtesting tool
- A-share backtesting tool
- free data source backtesting
- Local-first workflow: your data and backtest results stay on your machine
- Two-market coverage: validate US and A-share strategies in one workspace
- Free data sources: lower cost for strategy research and iteration
- Practical flow: data, strategy, history, and run in one console
- Manage market data and refresh quickly
- Create and manage strategies
- Review historical backtests and key results
- Launch new backtests and track progress
You can use Codex or Claude Code to edit backtest strategy files directly in the strategies/ folder.
- Strategy directory:
strategies/ - Engine-specific folders:
strategies/ziplinefor Zipline strategiesstrategies/rqalphafor RQAlpha strategies
- Typical workflow: ask Codex/Claude Code to create, update, or refactor strategy files, then run a backtest in the console
- Example request: "Update
/Users/sgcy/btrun/strategies/zipline/my_strategy.pyto add stop-loss and take-profit rules"
./bootstrap.sh
./start.shAfter startup:
- Web console: http://127.0.0.1:5173
- API docs: http://127.0.0.1:8000/docs
- Individual traders validating ideas quickly
- Quant researchers iterating with low infrastructure cost
- Developers who want a local, controllable backtesting workspace
AI Quant Terminal is not a cloud SaaS. It is your own local AI quant workspace:
- lightweight
- controllable
- built for continuous strategy iteration
If you want deeper engine/configuration details, see:
backend/frontend/docs/